Electrocardiogram (ECG) is the electrical representation of the contractile activity of the heart over time, which can be easily recorded using non-invasive electrodes on the chest or limbs. ECG indicates the overall rhythm of the heart and weaknesses in different parts of the heart muscle, and can measure and diagnose abnormal rhythms of the heart.
An ECG signal can be represented by a cyclic occurrence of patterns with different frequency content (QRS complexes, P and T waves). The different types of noise and interference can also be separated into different frequency bands.
Several well-documented signal processing algorithms exist that can separate an ECG signal into its different frequency bands. An example of a signal processing algorithm is wavelet transformation. Wavelet transform (WT) are mathematical functions that separate a signal into different frequency bands.
It is possible to apply different signal processing on different sub-bands to realize different functions. In known systems, for each of the different functions, a different signal processing algorithm is used to separate the ECG signal into its different frequency bands. This leads to an increase in the system size.
If many types of ECG signal processing can be integrated into one ASIC chip, the chip size can be quite small. There is thus a need to provide a compact ECG signal processing system which would be suitable for long-term monitoring